SPEECHMATICSSPEECH-TO-TEXT136,840 SAMPLES / 30 DAYSLAST RUN NOV 2, 2026, 09:00 UTC
Linden 1 speech-to-text benchmarks
Linden 1, hosted by Speechmatics, measures mean 254 ms time to final segment (20th of 28) and 3.8% word error rate (10th of 30) among STT systems. Results cover the last 30 days. Coval benchmarks hosted endpoints daily using a consistent evaluation methodology. Last measured .
Coval has active speech-to-text measurements for Linden 1, created by Speechmatics and served through Speechmatics's own API.
- Time to Final Segment#20 / 28
- 254ms
- Word Error Rate#10 / 30
- 3.8%
- Time to First Token#14 / 28
- 1528ms
Overview
Linden 1 is tested every day on fixed public audio — clean, accented, noisy, reverberant, far-field, clipped and phone-codec speech — for transcription accuracy and streaming latency.
Technical specifications
- Made by
- Speechmatics
- Hosted by
- Speechmatics
- Source
- Official API
- Licensing
- Proprietary
- Deployment
- Cloud
- Region
- Europe
- Features
- Diarization, Multilingual, VAD
How Linden 1 ranks
Full STT dashboard- #1Qwen3 ASR 1.7bDedicated inference. Shared endpoints serve many customers on the same infrastructure, while dedicated endpoints run on hardware reserved for a single customer.35 ms
- #12Whisper Large v3via BasetenDedicated inference. Shared endpoints serve many customers on the same infrastructure, while dedicated endpoints run on hardware reserved for a single customer.126 ms
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- #7Qwen3 ASR 1.7bDedicated inference. Shared endpoints serve many customers on the same infrastructure, while dedicated endpoints run on hardware reserved for a single customer.2.9%
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- #16Whisper Large v3via BasetenDedicated inference. Shared endpoints serve many customers on the same infrastructure, while dedicated endpoints run on hardware reserved for a single customer.4.5%
- #1Whisper Large v3via BasetenDedicated inference. Shared endpoints serve many customers on the same infrastructure, while dedicated endpoints run on hardware reserved for a single customer.914 ms
- #2Qwen3 ASR 1.7bDedicated inference. Shared endpoints serve many customers on the same infrastructure, while dedicated endpoints run on hardware reserved for a single customer.936 ms
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| # | Model | Host | TTFS | WER | TTFT | Samples |
|---|---|---|---|---|---|---|
| 1 | Qwen3 ASR 1.7b | Baseten | 35 ms | 936 ms | 13,678 | |
| 2 | STT RT v5 | Soniox | 44 ms | 1525 ms | 27,365 | |
| 3 | Qwen3 ASR Fast | Nari Labs | 50 ms | 1755 ms | 27,371 | |
| 4 | STT 1 | Inworld AI | 70 ms | 1026 ms | 27,334 | |
| 5 | Nova 3 | Deepgram | 85 ms | 1444 ms | 27,364 | |
| 6 | Nova 2 | Deepgram | 87 ms | 1427 ms | 27,311 | |
| 7 | Parakeet TDT 0.6B v3 | Together AI | 88 ms | 1197 ms | 15,445 | |
| 8 | Flux Multilingual | Deepgram | 100 ms | 1174 ms | 27,365 | |
| 9 | Flux | Deepgram | 101 ms | 1097 ms | 27,371 | |
| 10 | Universal 3.6 Pro | AssemblyAI | 114 ms | 1079 ms | 27,335 | |
| 11 | Scribe v2 Realtime | ElevenLabs | 118 ms | 2151 ms | 27,366 | |
| 12 | Whisper Large v3 | Baseten | 126 ms | 914 ms | 13,674 | |
| 13 | Universal 3.5 Pro | AssemblyAI | 126 ms | 1019 ms | 27,373 | |
| 14 | Ink 2 | Cartesia | 146 ms | 2034 ms | 27,369 | |
| 15 | Realtime Global | Reson8 | 159 ms | 2060 ms | 22,469 | |
| 16 | Whisper Large v3 | Together AI | 174 ms | 1210 ms | 15,513 | |
| 17 | Grok STT | SpaceXAI | 180 ms | — | 27,332 | |
| 18 | Pulse | Smallest | 203 ms | 1988 ms | 27,366 | |
| 19 | resonant-1 | Reson8 | 243 ms | — | 27,372 | |
| 20 | Linden 1 | Speechmatics | 254 ms | 1528 ms | 27,368 | |
| 21 | Default | Gradium | 261 ms | 2005 ms | 27,364 | |
| 22 | Gemini 3.5 Transcribe Live | Gemini | 383 ms | 1542 ms | 27,270 | |
| 23 | Daytona STT | Guava | 384 ms | 5651 ms | 13,133 | |
| 24 | Solaria 1 | Gladia | 414 ms | 1608 ms | 27,306 | |
| 25 | Voxtral Mini Transcribe Realtime 2602 | Mistral | 436 ms | 1867 ms | 20,731 | |
| 26 | GPT Realtime Whisper | OpenAI | 563 ms | 1822 ms | 26,862 | |
| 27 | Chirp 3 | 807 ms | 6007 ms | 27,330 | ||
| 28 | Chirp 2 | 895 ms | 6097 ms | 27,368 | ||
| — | Nemotron 3.5 ASR Streaming | Together AI | — | 1557 ms | 15,422 | |
| — | Universal Streaming | AssemblyAI | — | 1516 ms | 27,339 |
Highest relative placement: 10th of 30 on Word Error Rate.
Latency vs accuracy
Where the errors come from
- Linden 13.8%
Averages and tail latency
Averages hide slow outliers — these are the distributions behind each figure.
- Time to Final Segmentp50 229 ms · Max 21466 ms
- Time to First Tokenp50 1537 ms · Max 15599 ms
- Linden 1p50 0.0% · Max 100.0%
| Metric | Average | p25 | p50 | p75 | p90 | p95 | Max | Samples |
|---|---|---|---|---|---|---|---|---|
| Time to Final Segment | 254 ms | 218 ms | 229 ms | 259 ms | 346 ms | 368 ms | 21466 ms | 27,368 |
| Word Error Rate | 3.8% | 0.0% | 0.0% | 6.7% | 12.5% | 18.2% | 100.0% | 27,368 |
| Time to First Token | 1528 ms | 1144 ms | 1537 ms | 1681 ms | 2085 ms | 2386 ms | 15599 ms | 27,368 |
Last 30 days
Daily medians from the same measurement runs · gaps are days without qualifying runs.
Time to Final Segment by dataset
- PipeCat (production)244 ms
- WildASR clean247 ms
- WildASR noise gaps268 ms
- WildASR phone codec268 ms
- WildASR clipping273 ms
- WildASR accents293 ms
- WildASR far-field302 ms
| Dataset | TTFS | Samples |
|---|---|---|
| ProductionPipeCat | 244 ms | 14,409 |
| AccentsWildASR | 293 ms | 1,441 |
| CleanWildASR | 247 ms | 5,760 |
| ClippingWildASR | 273 ms | 1,441 |
| Far-fieldWildASR | 302 ms | 1,440 |
| Noise gapsWildASR | 268 ms | 1,439 |
| Phone codecWildASR | 268 ms | 1,438 |
Strongest condition: PipeCat (production) at 244 ms · weakest: WildASR far-field at 302 ms.
How fast is Linden 1?
On Speechmatics, Linden 1 measures mean 254 ms time to final segment (20th of 28) and mean 1528 ms time to first token (14th of 28). Last measured 2026-11-02.
How accurate is Linden 1?
On Speechmatics, Linden 1 measures 3.8% word error rate (10th of 30). Last measured 2026-11-02.
Who hosts Linden 1?
Linden 1 is created by Speechmatics and served by Speechmatics. Coval measures each hosted endpoint separately.
Results are re-measured daily using fixed datasets and reported over a rolling 30-day window. Same datasets, prompts and metric definitions for every model, measured by Coval’s open-source runner. Full methodology on the overview.
Evaluate your own voice agent
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